after_merge stringlengths 28 79.6k | before_merge stringlengths 20 79.6k | url stringlengths 38 71 | full_traceback stringlengths 43 922k | traceback_type stringclasses 555
values |
|---|---|---|---|---|
def main(args=None):
args = args or sys.argv[1:]
parser, resolver_options_builder = configure_clp()
try:
separator = args.index("--")
args, cmdline = args[:separator], args[separator + 1 :]
except ValueError:
args, cmdline = args, []
options, reqs = parser.parse_args(args=a... | def main(args=None):
args = args or sys.argv[1:]
parser, resolver_options_builder = configure_clp()
try:
separator = args.index("--")
args, cmdline = args[:separator], args[separator + 1 :]
except ValueError:
args, cmdline = args, []
options, reqs = parser.parse_args(args=a... | https://github.com/pantsbuild/pex/issues/260 | Traceback (most recent call last):
File ".tox/package/bin/pex", line 11, in <module>
sys.exit(main())
File ".../lib/python3.4/site-packages/pex/bin/pex.py", line 533, in main
options.cache_dir = make_relative_to_root(options.cache_dir)
File ".../.tox/package/lib/python3.4/site-packages/pex/bin/pex.py", line 514, in mak... | AttributeError |
def main(args=None):
args = args or sys.argv[1:]
parser, resolver_options_builder = configure_clp()
try:
separator = args.index("--")
args, cmdline = args[:separator], args[separator + 1 :]
except ValueError:
args, cmdline = args, []
options, reqs = parser.parse_args(args=a... | def main(args):
parser, resolver_options_builder = configure_clp()
try:
separator = args.index("--")
args, cmdline = args[:separator], args[separator + 1 :]
except ValueError:
args, cmdline = args, []
options, reqs = parser.parse_args(args=args)
if options.pex_root:
... | https://github.com/pantsbuild/pex/issues/252 | $ tox -e py27-package
GLOB sdist-make: /Users/billg/ws/git/pex/setup.py
py27-package inst-nodeps: /Users/billg/ws/git/pex/.tox/dist/pex-1.1.6.zip
py27-package installed: funcsigs==1.0.2,mock==2.0.0,pbr==1.9.1,pex==1.1.6,py==1.4.31,pytest==2.9.1,six==1.10.0,twitter.common.contextutil==0.3.4,twitter.common.dirutil==0.3.4... | TypeError |
def packages_from_requirement_cached(
local_iterator, ttl, iterator, requirement, *args, **kw
):
packages = packages_from_requirement(local_iterator, requirement, *args, **kw)
if packages:
# match with exact requirement, always accept.
if requirement_is_exact(requirement):
TRACE... | def packages_from_requirement_cached(
local_iterator, ttl, iterator, requirement, *args, **kw
):
packages = packages_from_requirement(local_iterator, requirement, *args, **kw)
if packages:
# match with exact requirement, always accept.
if requirement_is_exact(requirement):
TRACE... | https://github.com/pantsbuild/pex/issues/29 | mba=pex=; pex -r pytest -r setuptools -r py==1.4.25 -o /tmp/pt.pex --cache-ttl=3600 -v -v -v -v -v
pex: Package cache hit (inexact): pytest
pex: Package cache hit (inexact): setuptools
pex: Package cache miss: py==1.4.25
pex: Resolving distributions :: Fetching https://pypi.python.org/packages/source/p/py/py-1.4.25.tar... | OSError |
def resolve(
requirements,
fetchers=None,
translator=None,
interpreter=None,
platform=None,
context=None,
threads=1,
precedence=None,
cache=None,
cache_ttl=None,
):
"""Produce all distributions needed to (recursively) meet `requirements`
:param requirements: An iterator ... | def resolve(
requirements,
fetchers=None,
translator=None,
interpreter=None,
platform=None,
context=None,
threads=1,
precedence=None,
cache=None,
cache_ttl=None,
):
"""Produce all distributions needed to (recursively) meet `requirements`
:param requirements: An iterator ... | https://github.com/pantsbuild/pex/issues/29 | mba=pex=; pex -r pytest -r setuptools -r py==1.4.25 -o /tmp/pt.pex --cache-ttl=3600 -v -v -v -v -v
pex: Package cache hit (inexact): pytest
pex: Package cache hit (inexact): setuptools
pex: Package cache miss: py==1.4.25
pex: Resolving distributions :: Fetching https://pypi.python.org/packages/source/p/py/py-1.4.25.tar... | OSError |
def requires(package, requirement):
if not distributions.has(package):
with TRACER.timed("Fetching %s" % package.url, V=2):
local_package = Package.from_href(context.fetch(package, into=cache))
if package.remote:
# this was a remote resolution -- so if we copy from remote to ... | def requires(package, requirement):
if not distributions.has(package):
local_package = Package.from_href(context.fetch(package, into=cache))
if package.remote:
# this was a remote resolution -- so if we copy from remote to local but the
# local already existed, update the mti... | https://github.com/pantsbuild/pex/issues/29 | mba=pex=; pex -r pytest -r setuptools -r py==1.4.25 -o /tmp/pt.pex --cache-ttl=3600 -v -v -v -v -v
pex: Package cache hit (inexact): pytest
pex: Package cache hit (inexact): setuptools
pex: Package cache miss: py==1.4.25
pex: Resolving distributions :: Fetching https://pypi.python.org/packages/source/p/py/py-1.4.25.tar... | OSError |
def deserialize(collection, topological=True):
"""
Load a collection from file system.
:param collection: The collection to deserialize.
:param topological: If the collection list should be sorted by the
collection dict depth value or not.
:type topological: bool
"""
... | def deserialize(collection, topological=True):
"""
Load a collection from file system.
:param collection: The collection type the deserialize
:param topological: If the dict/list should be sorted or not.
:type topological: bool
"""
datastruct = deserialize_raw(collection.collection_types()... | https://github.com/cobbler/cobbler/issues/2259 | Traceback (most recent call last):
File "/usr/local/lib/python3.7/dist-packages/cobbler/cobbler_collections/manager.py", line 185, in deserialize
serializer.deserialize(collection)
File "/usr/local/lib/python3.7/dist-packages/cobbler/serializer.py", line 124, in deserialize
storage_module.deserialize(collection, topolo... | cobbler.cexceptions.CX |
def deserialize(collection, topological=True):
"""
Load a collection from the database.
:param collection: The collection to deserialize.
:param topological: If the collection list should be sorted by the
collection dict depth value or not.
:type topological: bool
"""
... | def deserialize(collection, topological=True):
"""
Load a collection from the database.
:param collection: The collection to deserialize.
:param topological: This sorts the returned dict.
:type topological: bool
"""
datastruct = deserialize_raw(collection.collection_type())
if topologi... | https://github.com/cobbler/cobbler/issues/2259 | Traceback (most recent call last):
File "/usr/local/lib/python3.7/dist-packages/cobbler/cobbler_collections/manager.py", line 185, in deserialize
serializer.deserialize(collection)
File "/usr/local/lib/python3.7/dist-packages/cobbler/serializer.py", line 124, in deserialize
storage_module.deserialize(collection, topolo... | cobbler.cexceptions.CX |
def deserialize(collection, topological=True):
"""
Load a collection from disk.
:param collection: The Cobbler collection to know the type of the item.
:param topological: Sort collection based on each items' depth attribute
in the list of collection items. This ensures
... | def deserialize(collection, topological=True):
"""
Load a collection from disk.
:param collection: The Cobbler collection to know the type of the item.
:param topological: Unkown parameter.
:type topological: bool
"""
__grab_lock()
storage_module = __get_storage_module(collection.collec... | https://github.com/cobbler/cobbler/issues/2259 | Traceback (most recent call last):
File "/usr/local/lib/python3.7/dist-packages/cobbler/cobbler_collections/manager.py", line 185, in deserialize
serializer.deserialize(collection)
File "/usr/local/lib/python3.7/dist-packages/cobbler/serializer.py", line 124, in deserialize
storage_module.deserialize(collection, topolo... | cobbler.cexceptions.CX |
def heats(diagrams, sampling, step_size, sigma):
# WARNING: modifies `diagrams` in place
heats_ = np.zeros((len(diagrams), len(sampling), len(sampling)), dtype=float)
# If the step size is zero, we return a trivial image
if step_size == 0:
return heats_
# Set the values outside of the sampl... | def heats(diagrams, sampling, step_size, sigma):
heats_ = np.zeros((diagrams.shape[0], sampling.shape[0], sampling.shape[0]))
diagrams[diagrams < sampling[0, 0]] = sampling[0, 0]
diagrams[diagrams > sampling[-1, 0]] = sampling[-1, 0]
diagrams = np.array((diagrams - sampling[0, 0]) / step_size, dtype=in... | https://github.com/giotto-ai/giotto-tda/issues/438 | ---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-5-5e233492b878> in <module>
----> 1 Amplitude(metric="persistence_image").fit_transform(Xd)
~\Workspace\giotto-tda_ulupo\gtda\utils\_docs.py in fit_tran... | TypeError |
def persistence_images(diagrams, sampling, step_size, sigma, weights):
# For persistence images, `sampling` is a tall matrix with two columns
# (the first for birth and the second for persistence), and `step_size` is
# a 2d array
# WARNING: modifies `diagrams` in place
persistence_images_ = np.zeros... | def persistence_images(diagrams, sampling, step_size, weights, sigma):
persistence_images_ = np.zeros(
(diagrams.shape[0], sampling.shape[0], sampling.shape[0])
)
# Transform diagrams from (birth, death, dim) to (birth, persistence, dim)
diagrams[:, :, 1] = diagrams[:, :, 1] - diagrams[:, :, 0]
... | https://github.com/giotto-ai/giotto-tda/issues/438 | ---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-5-5e233492b878> in <module>
----> 1 Amplitude(metric="persistence_image").fit_transform(Xd)
~\Workspace\giotto-tda_ulupo\gtda\utils\_docs.py in fit_tran... | TypeError |
def silhouettes(diagrams, sampling, power, **kwargs):
"""Input: a batch of persistence diagrams with a sampling (3d array
returned by _bin) of a one-dimensional range.
"""
sampling = np.transpose(sampling, axes=(1, 2, 0))
weights = np.diff(diagrams, axis=2)
if power > 8.0:
weights = weig... | def silhouettes(diagrams, sampling, power, **kwargs):
"""Input: a batch of persistence diagrams with a sampling (3d array
returned by _bin) of a one-dimensional range.
"""
sampling = np.transpose(sampling, axes=(1, 2, 0))
weights = np.diff(diagrams, axis=2)[:, :, [0]]
if power > 8.0:
wei... | https://github.com/giotto-ai/giotto-tda/issues/438 | ---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-5-5e233492b878> in <module>
----> 1 Amplitude(metric="persistence_image").fit_transform(Xd)
~\Workspace\giotto-tda_ulupo\gtda\utils\_docs.py in fit_tran... | TypeError |
def betti_distances(diagrams_1, diagrams_2, sampling, step_size, p=2.0, **kwargs):
step_size_factor = step_size ** (1 / p)
are_arrays_equal = np.array_equal(diagrams_1, diagrams_2)
betti_curves_1 = betti_curves(diagrams_1, sampling)
if are_arrays_equal:
distances = pdist(betti_curves_1, "minkows... | def betti_distances(diagrams_1, diagrams_2, sampling, step_size, p=2.0, **kwargs):
betti_curves_1 = betti_curves(diagrams_1, sampling)
if np.array_equal(diagrams_1, diagrams_2):
unnorm_dist = squareform(pdist(betti_curves_1, "minkowski", p=p))
return (step_size ** (1 / p)) * unnorm_dist
bett... | https://github.com/giotto-ai/giotto-tda/issues/438 | ---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-5-5e233492b878> in <module>
----> 1 Amplitude(metric="persistence_image").fit_transform(Xd)
~\Workspace\giotto-tda_ulupo\gtda\utils\_docs.py in fit_tran... | TypeError |
def landscape_distances(
diagrams_1, diagrams_2, sampling, step_size, p=2.0, n_layers=1, **kwargs
):
step_size_factor = step_size ** (1 / p)
n_samples_1, n_points_1 = diagrams_1.shape[:2]
n_layers_1 = min(n_layers, n_points_1)
if np.array_equal(diagrams_1, diagrams_2):
ls_1 = landscapes(diag... | def landscape_distances(
diagrams_1, diagrams_2, sampling, step_size, p=2.0, n_layers=1, **kwargs
):
n_samples_1, n_points_1 = diagrams_1.shape[:2]
n_layers_1 = min(n_layers, n_points_1)
if np.array_equal(diagrams_1, diagrams_2):
ls_1 = landscapes(diagrams_1, sampling, n_layers_1).reshape(n_samp... | https://github.com/giotto-ai/giotto-tda/issues/438 | ---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-5-5e233492b878> in <module>
----> 1 Amplitude(metric="persistence_image").fit_transform(Xd)
~\Workspace\giotto-tda_ulupo\gtda\utils\_docs.py in fit_tran... | TypeError |
def heat_distances(
diagrams_1, diagrams_2, sampling, step_size, sigma=0.1, p=2.0, **kwargs
):
# WARNING: `heats` modifies `diagrams` in place
step_size_factor = step_size ** (2 / p)
are_arrays_equal = np.array_equal(diagrams_1, diagrams_2)
heats_1 = heats(diagrams_1, sampling, step_size, sigma).res... | def heat_distances(
diagrams_1, diagrams_2, sampling, step_size, sigma=1.0, p=2.0, **kwargs
):
heat_1 = heats(diagrams_1, sampling, step_size, sigma).reshape(
diagrams_1.shape[0], -1
)
if np.array_equal(diagrams_1, diagrams_2):
unnorm_dist = squareform(pdist(heat_1, "minkowski", p=p))
... | https://github.com/giotto-ai/giotto-tda/issues/438 | ---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-5-5e233492b878> in <module>
----> 1 Amplitude(metric="persistence_image").fit_transform(Xd)
~\Workspace\giotto-tda_ulupo\gtda\utils\_docs.py in fit_tran... | TypeError |
def persistence_image_distances(
diagrams_1,
diagrams_2,
sampling,
step_size,
sigma=0.1,
weight_function=np.ones_like,
p=2.0,
**kwargs,
):
# For persistence images, `sampling` is a tall matrix with two columns
# (the first for birth and the second for persistence), and `step_size... | def persistence_image_distances(
diagrams_1,
diagrams_2,
sampling,
step_size,
weight_function=lambda x: x,
sigma=1.0,
p=2.0,
**kwargs,
):
sampling_ = np.copy(sampling.reshape((-1,)))
weights = weight_function(sampling_ - sampling_[0])
persistence_image_1 = persistence_images(... | https://github.com/giotto-ai/giotto-tda/issues/438 | ---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-5-5e233492b878> in <module>
----> 1 Amplitude(metric="persistence_image").fit_transform(Xd)
~\Workspace\giotto-tda_ulupo\gtda\utils\_docs.py in fit_tran... | TypeError |
def silhouette_distances(
diagrams_1, diagrams_2, sampling, step_size, power=1.0, p=2.0, **kwargs
):
step_size_factor = step_size ** (1 / p)
are_arrays_equal = np.array_equal(diagrams_1, diagrams_2)
silhouettes_1 = silhouettes(diagrams_1, sampling, power)
if are_arrays_equal:
distances = pdi... | def silhouette_distances(
diagrams_1, diagrams_2, sampling, step_size, power=2.0, p=2.0, **kwargs
):
silhouette_1 = silhouettes(diagrams_1, sampling, power)
if np.array_equal(diagrams_1, diagrams_2):
unnorm_dist = squareform(pdist(silhouette_1, "minkowski", p=p))
else:
silhouette_2 = sil... | https://github.com/giotto-ai/giotto-tda/issues/438 | ---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-5-5e233492b878> in <module>
----> 1 Amplitude(metric="persistence_image").fit_transform(Xd)
~\Workspace\giotto-tda_ulupo\gtda\utils\_docs.py in fit_tran... | TypeError |
def betti_amplitudes(diagrams, sampling, step_size, p=2.0, **kwargs):
step_size_factor = step_size ** (1 / p)
bcs = betti_curves(diagrams, sampling)
amplitudes = np.linalg.norm(bcs, axis=1, ord=p)
amplitudes *= step_size_factor
return amplitudes
| def betti_amplitudes(diagrams, sampling, step_size, p=2.0, **kwargs):
bcs = betti_curves(diagrams, sampling)
return (step_size ** (1 / p)) * np.linalg.norm(bcs, axis=1, ord=p)
| https://github.com/giotto-ai/giotto-tda/issues/438 | ---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-5-5e233492b878> in <module>
----> 1 Amplitude(metric="persistence_image").fit_transform(Xd)
~\Workspace\giotto-tda_ulupo\gtda\utils\_docs.py in fit_tran... | TypeError |
def landscape_amplitudes(diagrams, sampling, step_size, p=2.0, n_layers=1, **kwargs):
step_size_factor = step_size ** (1 / p)
ls = landscapes(diagrams, sampling, n_layers).reshape(len(diagrams), -1)
amplitudes = np.linalg.norm(ls, axis=1, ord=p)
amplitudes *= step_size_factor
return amplitudes
| def landscape_amplitudes(diagrams, sampling, step_size, p=2.0, n_layers=1, **kwargs):
ls = landscapes(diagrams, sampling, n_layers).reshape(len(diagrams), -1)
return (step_size ** (1 / p)) * np.linalg.norm(ls, axis=1, ord=p)
| https://github.com/giotto-ai/giotto-tda/issues/438 | ---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-5-5e233492b878> in <module>
----> 1 Amplitude(metric="persistence_image").fit_transform(Xd)
~\Workspace\giotto-tda_ulupo\gtda\utils\_docs.py in fit_tran... | TypeError |
def heat_amplitudes(diagrams, sampling, step_size, sigma=0.1, p=2.0, **kwargs):
# WARNING: `heats` modifies `diagrams` in place
step_size_factor = step_size ** (2 / p)
heats_ = heats(diagrams, sampling, step_size, sigma).reshape(len(diagrams), -1)
amplitudes = np.linalg.norm(heats_, axis=1, ord=p)
a... | def heat_amplitudes(diagrams, sampling, step_size, sigma=1.0, p=2.0, **kwargs):
heat = heats(diagrams, sampling, step_size, sigma)
return np.linalg.norm(heat, axis=(1, 2), ord=p)
| https://github.com/giotto-ai/giotto-tda/issues/438 | ---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-5-5e233492b878> in <module>
----> 1 Amplitude(metric="persistence_image").fit_transform(Xd)
~\Workspace\giotto-tda_ulupo\gtda\utils\_docs.py in fit_tran... | TypeError |
def persistence_image_amplitudes(
diagrams,
sampling,
step_size,
sigma=0.1,
weight_function=np.ones_like,
p=2.0,
**kwargs,
):
# For persistence images, `sampling` is a tall matrix with two columns
# (the first for birth and the second for persistence), and `step_size` is
# a 2d a... | def persistence_image_amplitudes(
diagrams,
sampling,
step_size,
weight_function=lambda x: x,
sigma=1.0,
p=2.0,
**kwargs,
):
persistence_image = persistence_images(
diagrams, sampling, step_size, weight_function, sigma
)
return np.linalg.norm(persistence_image, axis=(1, 2... | https://github.com/giotto-ai/giotto-tda/issues/438 | ---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-5-5e233492b878> in <module>
----> 1 Amplitude(metric="persistence_image").fit_transform(Xd)
~\Workspace\giotto-tda_ulupo\gtda\utils\_docs.py in fit_tran... | TypeError |
def silhouette_amplitudes(diagrams, sampling, step_size, power=1.0, p=2.0, **kwargs):
step_size_factor = step_size ** (1 / p)
silhouettes_ = silhouettes(diagrams, sampling, power)
amplitudes = np.linalg.norm(silhouettes_, axis=1, ord=p)
amplitudes *= step_size_factor
return amplitudes
| def silhouette_amplitudes(diagrams, sampling, step_size, power=2.0, p=2.0, **kwargs):
sht = silhouettes(diagrams, sampling, power)
return (step_size ** (1 / p)) * np.linalg.norm(sht, axis=1, ord=p)
| https://github.com/giotto-ai/giotto-tda/issues/438 | ---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-5-5e233492b878> in <module>
----> 1 Amplitude(metric="persistence_image").fit_transform(Xd)
~\Workspace\giotto-tda_ulupo\gtda\utils\_docs.py in fit_tran... | TypeError |
def _subdiagrams(X, homology_dimensions, remove_dim=False):
"""For each diagram in a collection, extract the subdiagrams in a given
list of homology dimensions. It is assumed that all diagrams in X contain
the same number of points in each homology dimension."""
n_samples = len(X)
X_0 = X[0]
de... | def _subdiagrams(X, homology_dimensions, remove_dim=False):
"""For each diagram in a collection, extract the subdiagrams in a given
list of homology dimensions. It is assumed that all diagrams in X contain
the same number of points in each homology dimension."""
n = len(X)
if len(homology_dimensions... | https://github.com/giotto-ai/giotto-tda/issues/438 | ---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-5-5e233492b878> in <module>
----> 1 Amplitude(metric="persistence_image").fit_transform(Xd)
~\Workspace\giotto-tda_ulupo\gtda\utils\_docs.py in fit_tran... | TypeError |
def _sample_image(image, diagram_pixel_coords):
# WARNING: Modifies `image` in-place
unique, counts = np.unique(diagram_pixel_coords, axis=0, return_counts=True)
unique = tuple(tuple(row) for row in unique.astype(np.int).T)
image[unique] = counts
| def _sample_image(image, sampled_diag):
# NOTE: Modifies `image` in-place
unique, counts = np.unique(sampled_diag, axis=0, return_counts=True)
unique = tuple(tuple(row) for row in unique.astype(np.int).T)
image[unique] = counts
| https://github.com/giotto-ai/giotto-tda/issues/438 | ---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-5-5e233492b878> in <module>
----> 1 Amplitude(metric="persistence_image").fit_transform(Xd)
~\Workspace\giotto-tda_ulupo\gtda\utils\_docs.py in fit_tran... | TypeError |
def _filter(X, filtered_homology_dimensions, cutoff):
n = len(X)
homology_dimensions = sorted(np.unique(X[0, :, 2]))
unfiltered_homology_dimensions = [
dim for dim in homology_dimensions if dim not in filtered_homology_dimensions
]
if len(unfiltered_homology_dimensions) == 0:
Xuf = ... | def _filter(X, filtered_homology_dimensions, cutoff):
n = len(X)
homology_dimensions = sorted(list(set(X[0, :, 2])))
unfiltered_homology_dimensions = [
dim for dim in homology_dimensions if dim not in filtered_homology_dimensions
]
if len(unfiltered_homology_dimensions) == 0:
Xuf = ... | https://github.com/giotto-ai/giotto-tda/issues/438 | ---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-5-5e233492b878> in <module>
----> 1 Amplitude(metric="persistence_image").fit_transform(Xd)
~\Workspace\giotto-tda_ulupo\gtda\utils\_docs.py in fit_tran... | TypeError |
def _bin(X, metric, n_bins=100, homology_dimensions=None, **kw_args):
if homology_dimensions is None:
homology_dimensions = sorted(np.unique(X[0, :, 2]))
# For some vectorizations, we force the values to be the same + widest
sub_diags = {
dim: _subdiagrams(X, [dim], remove_dim=True) for dim ... | def _bin(X, metric, n_bins=100, **kw_args):
homology_dimensions = sorted(list(set(X[0, :, 2])))
# For some vectorizations, we force the values to be the same + widest
sub_diags = {
dim: _subdiagrams(X, [dim], remove_dim=True) for dim in homology_dimensions
}
# For persistence images, move in... | https://github.com/giotto-ai/giotto-tda/issues/438 | ---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-5-5e233492b878> in <module>
----> 1 Amplitude(metric="persistence_image").fit_transform(Xd)
~\Workspace\giotto-tda_ulupo\gtda\utils\_docs.py in fit_tran... | TypeError |
def fit(self, X, y=None):
"""Store all observed homology dimensions in
:attr:`homology_dimensions_` and compute
:attr:`effective_metric_params`. Then, return the estimator.
This method is here to implement the usual scikit-learn API and hence
work in pipelines.
Parameters
----------
X ... | def fit(self, X, y=None):
"""Store all observed homology dimensions in
:attr:`homology_dimensions_` and compute
:attr:`effective_metric_params`. Then, return the estimator.
This method is here to implement the usual scikit-learn API and hence
work in pipelines.
Parameters
----------
X ... | https://github.com/giotto-ai/giotto-tda/issues/438 | ---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-5-5e233492b878> in <module>
----> 1 Amplitude(metric="persistence_image").fit_transform(Xd)
~\Workspace\giotto-tda_ulupo\gtda\utils\_docs.py in fit_tran... | TypeError |
def fit(self, X, y=None):
"""Store all observed homology dimensions in
:attr:`homology_dimensions_`. Then, return the estimator.
This method is here to implement the usual scikit-learn API and hence
work in pipelines.
Parameters
----------
X : ndarray of shape (n_samples, n_features, 3)
... | def fit(self, X, y=None):
"""Store all observed homology dimensions in
:attr:`homology_dimensions_`. Then, return the estimator.
This method is here to implement the usual scikit-learn API and hence
work in pipelines.
Parameters
----------
X : ndarray of shape (n_samples, n_features, 3)
... | https://github.com/giotto-ai/giotto-tda/issues/438 | ---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-5-5e233492b878> in <module>
----> 1 Amplitude(metric="persistence_image").fit_transform(Xd)
~\Workspace\giotto-tda_ulupo\gtda\utils\_docs.py in fit_tran... | TypeError |
def __init__(self, metric="landscape", metric_params=None, order=None, n_jobs=None):
self.metric = metric
self.metric_params = metric_params
self.order = order
self.n_jobs = n_jobs
| def __init__(self, metric="landscape", metric_params=None, order=2.0, n_jobs=None):
self.metric = metric
self.metric_params = metric_params
self.order = order
self.n_jobs = n_jobs
| https://github.com/giotto-ai/giotto-tda/issues/438 | ---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-5-5e233492b878> in <module>
----> 1 Amplitude(metric="persistence_image").fit_transform(Xd)
~\Workspace\giotto-tda_ulupo\gtda\utils\_docs.py in fit_tran... | TypeError |
def fit(self, X, y=None):
"""Store all observed homology dimensions in
:attr:`homology_dimensions_` and compute
:attr:`effective_metric_params`. Then, return the estimator.
This method is here to implement the usual scikit-learn API and hence
work in pipelines.
Parameters
----------
X ... | def fit(self, X, y=None):
"""Store all observed homology dimensions in
:attr:`homology_dimensions_` and compute
:attr:`effective_metric_params`. Then, return the estimator.
This method is here to implement the usual scikit-learn API and hence
work in pipelines.
Parameters
----------
X ... | https://github.com/giotto-ai/giotto-tda/issues/438 | ---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-5-5e233492b878> in <module>
----> 1 Amplitude(metric="persistence_image").fit_transform(Xd)
~\Workspace\giotto-tda_ulupo\gtda\utils\_docs.py in fit_tran... | TypeError |
def fit(self, X, y=None):
"""Store all observed homology dimensions in
:attr:`homology_dimensions_` and compute :attr:`scale_`.
Then, return the estimator.
Parameters
----------
X : ndarray of shape (n_samples, n_features, 3)
Input data. Array of persistence diagrams, each a collection ... | def fit(self, X, y=None):
"""Store all observed homology dimensions in
:attr:`homology_dimensions_` and compute :attr:`scale_`.
Then, return the estimator.
Parameters
----------
X : ndarray of shape (n_samples, n_features, 3)
Input data. Array of persistence diagrams, each a collection ... | https://github.com/giotto-ai/giotto-tda/issues/438 | ---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-5-5e233492b878> in <module>
----> 1 Amplitude(metric="persistence_image").fit_transform(Xd)
~\Workspace\giotto-tda_ulupo\gtda\utils\_docs.py in fit_tran... | TypeError |
def transform(self, X, y=None):
"""Divide all birth and death values in `X` by :attr:`scale_`.
Parameters
----------
X : ndarray of shape (n_samples, n_features, 3)
Input data. Array of persistence diagrams, each a collection of
triples [b, d, q] representing persistent topological feat... | def transform(self, X, y=None):
"""Divide all birth and death values in `X` by :attr:`scale_`.
Parameters
----------
X : ndarray of shape (n_samples, n_features, 3)
Input data. Array of persistence diagrams, each a collection of
triples [b, d, q] representing persistent topological feat... | https://github.com/giotto-ai/giotto-tda/issues/438 | ---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-5-5e233492b878> in <module>
----> 1 Amplitude(metric="persistence_image").fit_transform(Xd)
~\Workspace\giotto-tda_ulupo\gtda\utils\_docs.py in fit_tran... | TypeError |
def inverse_transform(self, X):
"""Scale back the data to the original representation. Multiplies by
the scale found in :meth:`fit`.
Parameters
----------
X : ndarray of shape (n_samples, n_features, 3)
Data to apply the inverse transform to, c.f. :meth:`transform`.
Returns
-------... | def inverse_transform(self, X):
"""Scale back the data to the original representation. Multiplies by
the scale found in :meth:`fit`.
Parameters
----------
X : ndarray of shape (n_samples, n_features, 3)
Data to apply the inverse transform to, c.f. :meth:`transform`.
Returns
-------... | https://github.com/giotto-ai/giotto-tda/issues/438 | ---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-5-5e233492b878> in <module>
----> 1 Amplitude(metric="persistence_image").fit_transform(Xd)
~\Workspace\giotto-tda_ulupo\gtda\utils\_docs.py in fit_tran... | TypeError |
def fit(self, X, y=None):
"""Store relevant homology dimensions in
:attr:`homology_dimensions_`. Then, return the estimator.
This method is here to implement the usual scikit-learn API and hence
work in pipelines.
Parameters
----------
X : ndarray of shape (n_samples, n_features, 3)
... | def fit(self, X, y=None):
"""Store relevant homology dimensions in
:attr:`homology_dimensions_`. Then, return the estimator.
This method is here to implement the usual scikit-learn API and hence
work in pipelines.
Parameters
----------
X : ndarray of shape (n_samples, n_features, 3)
... | https://github.com/giotto-ai/giotto-tda/issues/438 | ---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-5-5e233492b878> in <module>
----> 1 Amplitude(metric="persistence_image").fit_transform(Xd)
~\Workspace\giotto-tda_ulupo\gtda\utils\_docs.py in fit_tran... | TypeError |
def fit(self, X, y=None):
"""Store all observed homology dimensions in
:attr:`homology_dimensions_` and, for each dimension separately,
store evenly sample filtration parameter values in :attr:`samplings_`.
Then, return the estimator.
This method is here to implement the usual scikit-learn API and ... | def fit(self, X, y=None):
"""Store all observed homology dimensions in
:attr:`homology_dimensions_` and, for each dimension separately,
store evenly sample filtration parameter values in :attr:`samplings_`.
Then, return the estimator.
This method is here to implement the usual scikit-learn API and ... | https://github.com/giotto-ai/giotto-tda/issues/438 | ---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-5-5e233492b878> in <module>
----> 1 Amplitude(metric="persistence_image").fit_transform(Xd)
~\Workspace\giotto-tda_ulupo\gtda\utils\_docs.py in fit_tran... | TypeError |
def plot(self, Xt, sample=0, homology_dimensions=None, plotly_params=None):
"""Plot a sample from a collection of Betti curves arranged as in the
output of :meth:`transform`. Include homology in multiple dimensions.
Parameters
----------
Xt : ndarray of shape (n_samples, n_homology_dimensions, n_bi... | def plot(self, Xt, sample=0, homology_dimensions=None, plotly_params=None):
"""Plot a sample from a collection of Betti curves arranged as in
the output of :meth:`transform`. Include homology in multiple
dimensions.
Parameters
----------
Xt : ndarray of shape (n_samples, n_homology_dimensions, ... | https://github.com/giotto-ai/giotto-tda/issues/438 | ---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-5-5e233492b878> in <module>
----> 1 Amplitude(metric="persistence_image").fit_transform(Xd)
~\Workspace\giotto-tda_ulupo\gtda\utils\_docs.py in fit_tran... | TypeError |
def fit(self, X, y=None):
"""Store all observed homology dimensions in
:attr:`homology_dimensions_` and, for each dimension separately,
store evenly sample filtration parameter values in :attr:`samplings_`.
Then, return the estimator.
This method is here to implement the usual scikit-learn API and ... | def fit(self, X, y=None):
"""Store all observed homology dimensions in
:attr:`homology_dimensions_` and, for each dimension separately,
store evenly sample filtration parameter values in :attr:`samplings_`.
Then, return the estimator.
This method is here to implement the usual scikit-learn API and ... | https://github.com/giotto-ai/giotto-tda/issues/438 | ---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-5-5e233492b878> in <module>
----> 1 Amplitude(metric="persistence_image").fit_transform(Xd)
~\Workspace\giotto-tda_ulupo\gtda\utils\_docs.py in fit_tran... | TypeError |
def plot(self, Xt, sample=0, homology_dimensions=None, plotly_params=None):
"""Plot a sample from a collection of persistence landscapes arranged
as in the output of :meth:`transform`. Include homology in multiple
dimensions.
Parameters
----------
Xt : ndarray of shape (n_sa... | def plot(self, Xt, sample=0, homology_dimensions=None, plotly_params=None):
"""Plot a sample from a collection of persistence landscapes arranged
as in the output of :meth:`transform`. Include homology in multiple
dimensions.
Parameters
----------
Xt : ndarray of shape (n_sa... | https://github.com/giotto-ai/giotto-tda/issues/438 | ---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-5-5e233492b878> in <module>
----> 1 Amplitude(metric="persistence_image").fit_transform(Xd)
~\Workspace\giotto-tda_ulupo\gtda\utils\_docs.py in fit_tran... | TypeError |
def __init__(self, sigma=0.1, n_bins=100, n_jobs=None):
self.sigma = sigma
self.n_bins = n_bins
self.n_jobs = n_jobs
| def __init__(self, sigma=1.0, n_bins=100, n_jobs=None):
self.sigma = sigma
self.n_bins = n_bins
self.n_jobs = n_jobs
| https://github.com/giotto-ai/giotto-tda/issues/438 | ---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-5-5e233492b878> in <module>
----> 1 Amplitude(metric="persistence_image").fit_transform(Xd)
~\Workspace\giotto-tda_ulupo\gtda\utils\_docs.py in fit_tran... | TypeError |
def fit(self, X, y=None):
"""Store all observed homology dimensions in
:attr:`homology_dimensions_` and, for each dimension separately,
store evenly sample filtration parameter values in :attr:`samplings_`.
Then, return the estimator.
This method is here to implement the usual scikit-learn API and ... | def fit(self, X, y=None):
"""Store all observed homology dimensions in
:attr:`homology_dimensions_` and, for each dimension separately,
store evenly sample filtration parameter values in :attr:`samplings_`.
Then, return the estimator.
This method is here to implement the usual scikit-learn API and ... | https://github.com/giotto-ai/giotto-tda/issues/438 | ---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-5-5e233492b878> in <module>
----> 1 Amplitude(metric="persistence_image").fit_transform(Xd)
~\Workspace\giotto-tda_ulupo\gtda\utils\_docs.py in fit_tran... | TypeError |
def plot(
self, Xt, sample=0, homology_dimension_idx=0, colorscale="blues", plotly_params=None
):
"""Plot a single channel –- corresponding to a given homology
dimension -- in a sample from a collection of heat kernel images.
Parameters
----------
Xt : ndarray of shape (n_sample... | def plot(
self, Xt, sample=0, homology_dimension_idx=0, colorscale="blues", plotly_params=None
):
"""Plot a single channel – corresponding to a given homology
dimension – in a sample from a collection of heat kernel images.
Parameters
----------
Xt : ndarray of shape (n_samples,... | https://github.com/giotto-ai/giotto-tda/issues/438 | ---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-5-5e233492b878> in <module>
----> 1 Amplitude(metric="persistence_image").fit_transform(Xd)
~\Workspace\giotto-tda_ulupo\gtda\utils\_docs.py in fit_tran... | TypeError |
def __init__(self, sigma=0.1, n_bins=100, weight_function=None, n_jobs=None):
self.sigma = sigma
self.n_bins = n_bins
self.weight_function = weight_function
self.n_jobs = n_jobs
| def __init__(self, sigma=1.0, n_bins=100, weight_function=None, n_jobs=None):
self.sigma = sigma
self.n_bins = n_bins
self.weight_function = weight_function
self.n_jobs = n_jobs
| https://github.com/giotto-ai/giotto-tda/issues/438 | ---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-5-5e233492b878> in <module>
----> 1 Amplitude(metric="persistence_image").fit_transform(Xd)
~\Workspace\giotto-tda_ulupo\gtda\utils\_docs.py in fit_tran... | TypeError |
def fit(self, X, y=None):
"""Store all observed homology dimensions in
:attr:`homology_dimensions_` and, for each dimension separately,
store evenly sample filtration parameter values in :attr:`samplings_`.
Then, return the estimator.
This method is here to implement the usual scikit-learn API and ... | def fit(self, X, y=None):
"""Store all observed homology dimensions in
:attr:`homology_dimensions_` and, for each dimension separately,
store evenly sample filtration parameter values in :attr:`samplings_`.
Then, return the estimator.
This method is here to implement the usual scikit-learn API and ... | https://github.com/giotto-ai/giotto-tda/issues/438 | ---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-5-5e233492b878> in <module>
----> 1 Amplitude(metric="persistence_image").fit_transform(Xd)
~\Workspace\giotto-tda_ulupo\gtda\utils\_docs.py in fit_tran... | TypeError |
def transform(self, X, y=None):
"""Compute multi-channel raster images from diagrams in `X` by
convolution with a Gaussian kernel.
Parameters
----------
X : ndarray of shape (n_samples, n_features, 3)
Input data. Array of persistence diagrams, each a collection of
... | def transform(self, X, y=None):
"""Compute multi-channel raster images from diagrams in `X` by
convolution with a Gaussian kernel.
Parameters
----------
X : ndarray of shape (n_samples, n_features, 3)
Input data. Array of persistence diagrams, each a collection of
... | https://github.com/giotto-ai/giotto-tda/issues/438 | ---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-5-5e233492b878> in <module>
----> 1 Amplitude(metric="persistence_image").fit_transform(Xd)
~\Workspace\giotto-tda_ulupo\gtda\utils\_docs.py in fit_tran... | TypeError |
def plot(
self, Xt, sample=0, homology_dimension_idx=0, colorscale="blues", plotly_params=None
):
"""Plot a single channel -– corresponding to a given homology
dimension -– in a sample from a collection of persistence images.
Parameters
----------
Xt : ndarray of shape (n_sample... | def plot(
self, Xt, sample=0, homology_dimension_idx=0, colorscale="blues", plotly_params=None
):
"""Plot a single channel – corresponding to a given homology
dimension – in a sample from a collection of persistence images.
Parameters
----------
Xt : ndarray of shape (n_samples,... | https://github.com/giotto-ai/giotto-tda/issues/438 | ---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-5-5e233492b878> in <module>
----> 1 Amplitude(metric="persistence_image").fit_transform(Xd)
~\Workspace\giotto-tda_ulupo\gtda\utils\_docs.py in fit_tran... | TypeError |
def fit(self, X, y=None):
"""Store all observed homology dimensions in
:attr:`homology_dimensions_` and, for each dimension separately,
store evenly sample filtration parameter values in :attr:`samplings_`.
Then, return the estimator.
This method is here to implement the usual scikit-learn API and ... | def fit(self, X, y=None):
"""Store all observed homology dimensions in
:attr:`homology_dimensions_` and, for each dimension separately,
store evenly sample filtration parameter values in :attr:`samplings_`.
Then, return the estimator.
This method is here to implement the usual scikit-learn API and ... | https://github.com/giotto-ai/giotto-tda/issues/438 | ---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-5-5e233492b878> in <module>
----> 1 Amplitude(metric="persistence_image").fit_transform(Xd)
~\Workspace\giotto-tda_ulupo\gtda\utils\_docs.py in fit_tran... | TypeError |
def plot(self, Xt, sample=0, homology_dimensions=None, plotly_params=None):
"""Plot a sample from a collection of silhouettes arranged as in the
output of :meth:`transform`. Include homology in multiple dimensions.
Parameters
----------
Xt : ndarray of shape (n_samples, n_homology_dimensions, n_bin... | def plot(self, Xt, sample=0, homology_dimensions=None, plotly_params=None):
"""Plot a sample from a collection of silhouettes arranged as in
the output of :meth:`transform`. Include homology in multiple
dimensions.
Parameters
----------
Xt : ndarray of shape (n_samples, n_homology_dimensions, n... | https://github.com/giotto-ai/giotto-tda/issues/438 | ---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-5-5e233492b878> in <module>
----> 1 Amplitude(metric="persistence_image").fit_transform(Xd)
~\Workspace\giotto-tda_ulupo\gtda\utils\_docs.py in fit_tran... | TypeError |
def plot_diagram(diagram, homology_dimensions=None, plotly_params=None):
"""Plot a single persistence diagram.
Parameters
----------
diagram : ndarray of shape (n_points, 3)
The persistence diagram to plot, where the third dimension along axis 1
contains homology dimensions, and the fir... | def plot_diagram(diagram, homology_dimensions=None, plotly_params=None):
"""Plot a single persistence diagram.
Parameters
----------
diagram : ndarray of shape (n_points, 3)
The persistence diagram to plot, where the third dimension along axis 1
contains homology dimensions, and the fir... | https://github.com/giotto-ai/giotto-tda/issues/438 | ---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-5-5e233492b878> in <module>
----> 1 Amplitude(metric="persistence_image").fit_transform(Xd)
~\Workspace\giotto-tda_ulupo\gtda\utils\_docs.py in fit_tran... | TypeError |
def check_diagrams(X, copy=False):
"""Input validation for collections of persistence diagrams.
Basic type and sanity checks are run on the input collection and the
array is converted to float type before returning. In particular,
the input is checked to be an ndarray of shape ``(n_samples, n_points,
... | def check_diagrams(X, copy=False):
"""Input validation for collections of persistence diagrams.
Basic type and sanity checks are run on the input collection and the
array is converted to float type before returning. In particular,
the input is checked to be an ndarray of shape ``(n_samples, n_points,
... | https://github.com/giotto-ai/giotto-tda/issues/438 | ---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-5-5e233492b878> in <module>
----> 1 Amplitude(metric="persistence_image").fit_transform(Xd)
~\Workspace\giotto-tda_ulupo\gtda\utils\_docs.py in fit_tran... | TypeError |
def _heat(image, sampled_diag, sigma):
_sample_image(image, sampled_diag)
image[:] = gaussian_filter(image, sigma, mode="reflect")
| def _heat(image, sampled_diag, sigma):
_sample_image(image, sampled_diag) # modifies `heat` inplace
image[:] = gaussian_filter(image, sigma, mode="reflect")
| https://github.com/giotto-ai/giotto-tda/issues/427 | ---------------------------------------------------------------------------
_RemoteTraceback Traceback (most recent call last)
_RemoteTraceback:
"""
Traceback (most recent call last):
File "C:\Users\nicho\Anaconda3\lib\site-packages\joblib\externals\loky\process_executor.py", line 418, in _p... | ValueError |
def _parallel_pairwise(X1, X2, metric, metric_params, homology_dimensions, n_jobs):
metric_func = implemented_metric_recipes[metric]
effective_metric_params = metric_params.copy()
none_dict = {dim: None for dim in homology_dimensions}
samplings = effective_metric_params.pop("samplings", none_dict)
s... | def _parallel_pairwise(X1, X2, metric, metric_params, homology_dimensions, n_jobs):
metric_func = implemented_metric_recipes[metric]
effective_metric_params = metric_params.copy()
none_dict = {dim: None for dim in homology_dimensions}
samplings = effective_metric_params.pop("samplings", none_dict)
s... | https://github.com/giotto-ai/giotto-tda/issues/427 | ---------------------------------------------------------------------------
_RemoteTraceback Traceback (most recent call last)
_RemoteTraceback:
"""
Traceback (most recent call last):
File "C:\Users\nicho\Anaconda3\lib\site-packages\joblib\externals\loky\process_executor.py", line 418, in _p... | ValueError |
def _parallel_amplitude(X, metric, metric_params, homology_dimensions, n_jobs):
amplitude_func = implemented_amplitude_recipes[metric]
effective_metric_params = metric_params.copy()
none_dict = {dim: None for dim in homology_dimensions}
samplings = effective_metric_params.pop("samplings", none_dict)
... | def _parallel_amplitude(X, metric, metric_params, homology_dimensions, n_jobs):
amplitude_func = implemented_amplitude_recipes[metric]
effective_metric_params = metric_params.copy()
none_dict = {dim: None for dim in homology_dimensions}
samplings = effective_metric_params.pop("samplings", none_dict)
... | https://github.com/giotto-ai/giotto-tda/issues/427 | ---------------------------------------------------------------------------
_RemoteTraceback Traceback (most recent call last)
_RemoteTraceback:
"""
Traceback (most recent call last):
File "C:\Users\nicho\Anaconda3\lib\site-packages\joblib\externals\loky\process_executor.py", line 418, in _p... | ValueError |
def _sample_image(image, sampled_diag):
# NOTE: Modifies `image` in-place
unique, counts = np.unique(sampled_diag, axis=0, return_counts=True)
unique = tuple(tuple(row) for row in unique.astype(np.int).T)
image[unique] = counts
| def _sample_image(image, sampled_diag):
unique, counts = np.unique(sampled_diag, axis=0, return_counts=True)
unique = tuple(tuple(row) for row in unique.astype(np.int).T)
image[unique] = counts
| https://github.com/giotto-ai/giotto-tda/issues/427 | ---------------------------------------------------------------------------
_RemoteTraceback Traceback (most recent call last)
_RemoteTraceback:
"""
Traceback (most recent call last):
File "C:\Users\nicho\Anaconda3\lib\site-packages\joblib\externals\loky\process_executor.py", line 418, in _p... | ValueError |
def transform(self, X, y=None):
"""Compute the persistence entropies of diagrams in `X`.
Parameters
----------
X : ndarray of shape (n_samples, n_features, 3)
Input data. Array of persistence diagrams, each a collection of
triples [b, d, q] representing persistent topological features
... | def transform(self, X, y=None):
"""Compute the persistence entropies of diagrams in `X`.
Parameters
----------
X : ndarray of shape (n_samples, n_features, 3)
Input data. Array of persistence diagrams, each a collection of
triples [b, d, q] representing persistent topological features
... | https://github.com/giotto-ai/giotto-tda/issues/427 | ---------------------------------------------------------------------------
_RemoteTraceback Traceback (most recent call last)
_RemoteTraceback:
"""
Traceback (most recent call last):
File "C:\Users\nicho\Anaconda3\lib\site-packages\joblib\externals\loky\process_executor.py", line 418, in _p... | ValueError |
def transform(self, X, y=None):
"""Compute the Betti curves of diagrams in `X`.
Parameters
----------
X : ndarray of shape (n_samples, n_features, 3)
Input data. Array of persistence diagrams, each a collection of
triples [b, d, q] representing persistent topological features
th... | def transform(self, X, y=None):
"""Compute the Betti curves of diagrams in `X`.
Parameters
----------
X : ndarray of shape (n_samples, n_features, 3)
Input data. Array of persistence diagrams, each a collection of
triples [b, d, q] representing persistent topological features
th... | https://github.com/giotto-ai/giotto-tda/issues/427 | ---------------------------------------------------------------------------
_RemoteTraceback Traceback (most recent call last)
_RemoteTraceback:
"""
Traceback (most recent call last):
File "C:\Users\nicho\Anaconda3\lib\site-packages\joblib\externals\loky\process_executor.py", line 418, in _p... | ValueError |
def transform(self, X, y=None):
"""Compute the persistence landscapes of diagrams in `X`.
Parameters
----------
X : ndarray of shape (n_samples, n_features, 3)
Input data. Array of persistence diagrams, each a collection of
triples [b, d, q] representing persistent t... | def transform(self, X, y=None):
"""Compute the persistence landscapes of diagrams in `X`.
Parameters
----------
X : ndarray of shape (n_samples, n_features, 3)
Input data. Array of persistence diagrams, each a collection of
triples [b, d, q] representing persistent t... | https://github.com/giotto-ai/giotto-tda/issues/427 | ---------------------------------------------------------------------------
_RemoteTraceback Traceback (most recent call last)
_RemoteTraceback:
"""
Traceback (most recent call last):
File "C:\Users\nicho\Anaconda3\lib\site-packages\joblib\externals\loky\process_executor.py", line 418, in _p... | ValueError |
def transform(self, X, y=None):
"""Compute multi-channel raster images from diagrams in `X` by
convolution with a Gaussian kernel and reflection about the diagonal.
Parameters
----------
X : ndarray of shape (n_samples, n_features, 3)
Input data. Array of persistence dia... | def transform(self, X, y=None):
"""Compute multi-channel raster images from diagrams in `X` by
convolution with a Gaussian kernel and reflection about the diagonal.
Parameters
----------
X : ndarray of shape (n_samples, n_features, 3)
Input data. Array of persistence dia... | https://github.com/giotto-ai/giotto-tda/issues/427 | ---------------------------------------------------------------------------
_RemoteTraceback Traceback (most recent call last)
_RemoteTraceback:
"""
Traceback (most recent call last):
File "C:\Users\nicho\Anaconda3\lib\site-packages\joblib\externals\loky\process_executor.py", line 418, in _p... | ValueError |
def transform(self, X, y=None):
"""Compute multi-channel raster images from diagrams in `X` by
convolution with a Gaussian kernel.
Parameters
----------
X : ndarray of shape (n_samples, n_features, 3)
Input data. Array of persistence diagrams, each a collection of
... | def transform(self, X, y=None):
"""Compute multi-channel raster images from diagrams in `X` by
convolution with a Gaussian kernel.
Parameters
----------
X : ndarray of shape (n_samples, n_features, 3)
Input data. Array of persistence diagrams, each a collection of
... | https://github.com/giotto-ai/giotto-tda/issues/427 | ---------------------------------------------------------------------------
_RemoteTraceback Traceback (most recent call last)
_RemoteTraceback:
"""
Traceback (most recent call last):
File "C:\Users\nicho\Anaconda3\lib\site-packages\joblib\externals\loky\process_executor.py", line 418, in _p... | ValueError |
def transform(self, X, y=None):
"""Compute silhouettes of diagrams in `X`.
Parameters
----------
X : ndarray of shape (n_samples, n_features, 3)
Input data. Array of persistence diagrams, each a collection of
triples [b, d, q] representing persistent topological features
through... | def transform(self, X, y=None):
"""Compute silhouettes of diagrams in `X`.
Parameters
----------
X : ndarray of shape (n_samples, n_features, 3)
Input data. Array of persistence diagrams, each a collection of
triples [b, d, q] representing persistent topological features
through... | https://github.com/giotto-ai/giotto-tda/issues/427 | ---------------------------------------------------------------------------
_RemoteTraceback Traceback (most recent call last)
_RemoteTraceback:
"""
Traceback (most recent call last):
File "C:\Users\nicho\Anaconda3\lib\site-packages\joblib\externals\loky\process_executor.py", line 418, in _p... | ValueError |
def plot_diagram(diagram, homology_dimensions=None, **input_layout):
"""Plot a single persistence diagram.
Parameters
----------
diagram : ndarray of shape (n_points, 3)
The persistence diagram to plot, where the third dimension along axis 1
contains homology dimensions, and the first t... | def plot_diagram(diagram, homology_dimensions=None, **input_layout):
"""Plot a single persistence diagram.
Parameters
----------
diagram : ndarray of shape (n_points, 3)
The persistence diagram to plot, where the third dimension along axis 1
contains homology dimensions, and the first t... | https://github.com/giotto-ai/giotto-tda/issues/427 | ---------------------------------------------------------------------------
_RemoteTraceback Traceback (most recent call last)
_RemoteTraceback:
"""
Traceback (most recent call last):
File "C:\Users\nicho\Anaconda3\lib\site-packages\joblib\externals\loky\process_executor.py", line 418, in _p... | ValueError |
def caller_attributes(cls, module_name: str = "") -> Tuple[str, str, str]:
"""
Determine extra or changed fields for the caller.
1. qualname finds the relevant object and its __qualname__
2. caller_class_names is just the full class names of the calling
class if relevant.
3. module is munged i... | def caller_attributes(cls, module_name: str = "") -> Tuple[str, str, str]:
"""
Determine extra or changed fields for the caller.
1. qualname finds the relevant object and its __qualname__
2. caller_class_names is just the full class names of the calling
class if relevant.
3. module is munged i... | https://github.com/EDCD/EDMarketConnector/issues/808 | File "/home/ash/.local/share/EDMarketConnector/plugins/edrodent/load.py", line 38, in ready_to_rat
logger.debug("ready_to_rat: %r %r %r %r %r", self.open, self.low_fuel, self.hud_in_analysis_mode, self.has_fuel_transfer_limpet_controller, self.limpets)
File "/usr/local/lib/python3.7/logging/__init__.py", line 1366, in ... | RecursionError |
def __init__(self):
logger.debug("A call from A.B.__init__")
self.__test()
_ = self.test_prop
| def __init__(self):
logger.debug("A call from A.B.__init__")
self.__test()
| https://github.com/EDCD/EDMarketConnector/issues/808 | File "/home/ash/.local/share/EDMarketConnector/plugins/edrodent/load.py", line 38, in ready_to_rat
logger.debug("ready_to_rat: %r %r %r %r %r", self.open, self.low_fuel, self.hud_in_analysis_mode, self.has_fuel_transfer_limpet_controller, self.limpets)
File "/usr/local/lib/python3.7/logging/__init__.py", line 1366, in ... | RecursionError |
def caller_attributes(cls, module_name: str = "") -> Tuple[str, str, str]: # noqa: CCR001, E501 # this is as refactored as is sensible
"""
Determine extra or changed fields for the caller.
1. qualname finds the relevant object and its __qualname__
2. caller_class_names is just the full class names of ... | def caller_attributes(cls, module_name: str = "") -> Tuple[str, str, str]: # noqa: CCR001, E501 # this is as refactored as is sensible
"""
Determine extra or changed fields for the caller.
1. qualname finds the relevant object and its __qualname__
2. caller_class_names is just the full class names of ... | https://github.com/EDCD/EDMarketConnector/issues/808 | File "/home/ash/.local/share/EDMarketConnector/plugins/edrodent/load.py", line 38, in ready_to_rat
logger.debug("ready_to_rat: %r %r %r %r %r", self.open, self.low_fuel, self.hud_in_analysis_mode, self.has_fuel_transfer_limpet_controller, self.limpets)
File "/usr/local/lib/python3.7/logging/__init__.py", line 1366, in ... | RecursionError |
def caller_attributes(cls, module_name: str = "") -> Tuple[str, str, str]:
"""
Determine extra or changed fields for the caller.
1. qualname finds the relevant object and its __qualname__
2. caller_class_names is just the full class names of the calling
class if relevant.
3. module is munged i... | def caller_attributes(cls, module_name: str = "") -> Tuple[str, str, str]:
"""
Determine extra or changed fields for the caller.
1. qualname finds the relevant object and its __qualname__
2. caller_class_names is just the full class names of the calling
class if relevant.
3. module is munged i... | https://github.com/EDCD/EDMarketConnector/issues/808 | File "/home/ash/.local/share/EDMarketConnector/plugins/edrodent/load.py", line 38, in ready_to_rat
logger.debug("ready_to_rat: %r %r %r %r %r", self.open, self.low_fuel, self.hud_in_analysis_mode, self.has_fuel_transfer_limpet_controller, self.limpets)
File "/usr/local/lib/python3.7/logging/__init__.py", line 1366, in ... | RecursionError |
def caller_attributes(cls, module_name: str = "") -> Tuple[str, str, str]: # noqa: CCR001, E501 # this is as refactored as is sensible
"""
Determine extra or changed fields for the caller.
1. qualname finds the relevant object and its __qualname__
2. caller_class_names is just the full class names of ... | def caller_attributes(cls, module_name: str = "") -> Tuple[str, str, str]: # noqa: CCR001, E501 # this is as refactored as is sensible
"""
Determine extra or changed fields for the caller.
1. qualname finds the relevant object and its __qualname__
2. caller_class_names is just the full class names of ... | https://github.com/EDCD/EDMarketConnector/issues/764 | Exception in thread Thread-2:
Traceback (most recent call last):
File "/usr/local/lib/python3.7/threading.py", line 926, in _bootstrap_inner
self.run()
File "/usr/local/lib/python3.7/threading.py", line 870, in run
self._target(*self._args, **self._kwargs)
File "/home/ash/.local/share/EDMarketConnector/plugins/edmcover... | AttributeError |
def __init__(self):
logger.debug("A call from A.B.__init__")
self.__test()
| def __init__(self):
logger.debug("A call from A.B.__init__")
| https://github.com/EDCD/EDMarketConnector/issues/764 | Exception in thread Thread-2:
Traceback (most recent call last):
File "/usr/local/lib/python3.7/threading.py", line 926, in _bootstrap_inner
self.run()
File "/usr/local/lib/python3.7/threading.py", line 870, in run
self._target(*self._args, **self._kwargs)
File "/home/ash/.local/share/EDMarketConnector/plugins/edmcover... | AttributeError |
def caller_attributes(cls, module_name: str = "") -> Tuple[str, str, str]:
"""
Determine extra or changed fields for the caller.
1. qualname finds the relevant object and its __qualname__
2. caller_class_names is just the full class names of the calling
class if relevant.
3. module is munged i... | def caller_attributes(cls, module_name: str = "") -> Tuple[str, str, str]:
"""
Determine extra or changed fields for the caller.
1. qualname finds the relevant object and its __qualname__
2. caller_class_names is just the full class names of the calling
class if relevant.
3. module is munged i... | https://github.com/EDCD/EDMarketConnector/issues/764 | Exception in thread Thread-2:
Traceback (most recent call last):
File "/usr/local/lib/python3.7/threading.py", line 926, in _bootstrap_inner
self.run()
File "/usr/local/lib/python3.7/threading.py", line 870, in run
self._target(*self._args, **self._kwargs)
File "/home/ash/.local/share/EDMarketConnector/plugins/edmcover... | AttributeError |
def export_outfitting(self, data: Mapping[str, Any], is_beta: bool) -> None:
"""
export_outfitting updates EDDN with the current (lastStarport) station's outfitting options, if any.
Once the send is complete, this.outfitting is updated with the given data.
:param data: dict containing the outfitting da... | def export_outfitting(self, data: Mapping[str, Any], is_beta: bool) -> None:
"""
export_outfitting updates EDDN with the current (lastStarport) station's outfitting options, if any.
Once the send is complete, this.outfitting is updated with the given data.
:param data: dict containing the outfitting da... | https://github.com/EDCD/EDMarketConnector/issues/671 | 2020-08-21 13:06:28.140 - DEBUG - plugins.eddn.cmdr_data:726: Failed exporting data
Traceback (most recent call last):
File "/home/ad/development/python/EDMarketConnector/plugins/eddn.py", line 716, in cmdr_data
this.eddn.export_shipyard(data, is_beta)
File "/home/ad/development/python/EDMarketConnector/plugins/eddn.py... | AttributeError |
def export_shipyard(self, data: Dict[str, Any], is_beta: bool) -> None:
"""
export_shipyard updates EDDN with the current (lastStarport) station's outfitting options, if any.
once the send is complete, this.shipyard is updated to the new data.
:param data: dict containing the shipyard data
:param i... | def export_shipyard(self, data: Dict[str, Any], is_beta: bool) -> None:
"""
export_shipyard updates EDDN with the current (lastStarport) station's outfitting options, if any.
once the send is complete, this.shipyard is updated to the new data.
:param data: dict containing the shipyard data
:param i... | https://github.com/EDCD/EDMarketConnector/issues/671 | 2020-08-21 13:06:28.140 - DEBUG - plugins.eddn.cmdr_data:726: Failed exporting data
Traceback (most recent call last):
File "/home/ad/development/python/EDMarketConnector/plugins/eddn.py", line 716, in cmdr_data
this.eddn.export_shipyard(data, is_beta)
File "/home/ad/development/python/EDMarketConnector/plugins/eddn.py... | AttributeError |
def is_horizons(economies: MAP_STR_ANY, modules: Dict, ships: MAP_STR_ANY) -> bool:
return (
any(economy["name"] == "Colony" for economy in economies.values())
or any(module.get("sku") == HORIZ_SKU for module in modules.values())
or any(
ship.get("sku") == HORIZ_SKU
f... | def is_horizons(
economies: MAP_STR_ANY, modules: MAP_STR_ANY, ships: MAP_STR_ANY
) -> bool:
return (
any(economy["name"] == "Colony" for economy in economies.values())
or any(module.get("sku") == HORIZ_SKU for module in modules.values())
or any(
ship.get("sku") == HORIZ_SKU
... | https://github.com/EDCD/EDMarketConnector/issues/671 | 2020-08-21 13:06:28.140 - DEBUG - plugins.eddn.cmdr_data:726: Failed exporting data
Traceback (most recent call last):
File "/home/ad/development/python/EDMarketConnector/plugins/eddn.py", line 716, in cmdr_data
this.eddn.export_shipyard(data, is_beta)
File "/home/ad/development/python/EDMarketConnector/plugins/eddn.py... | AttributeError |
def start(self, root):
self.root = root
journal_dir = config.get("journaldir") or config.default_journal_dir
if journal_dir is None:
journal_dir = ""
# TODO(A_D): this is ignored for type checking due to all the different types config.get returns
# When that is refactored, remove the magic... | def start(self, root):
self.root = root
logdir = expanduser(config.get("journaldir") or config.default_journal_dir) # type: ignore # config is weird
if not logdir or not isdir(logdir): # type: ignore # config does weird things in its get
self.stop()
return False
if self.currentdir an... | https://github.com/EDCD/EDMarketConnector/issues/639 | PS /home/[1000]/edmc> ./EDMarketConnector.py
loading plugin coriolis from "/home/chr0me/edmc/plugins/coriolis.py"
loading plugin eddb from "/home/chr0me/edmc/plugins/eddb.py"
loading plugin eddn from "/home/chr0me/edmc/plugins/eddn.py"
loading plugin edsm from "/home/chr0me/edmc/plugins/edsm.py"
loading plugin edsy fro... | TypeError |
def __init__(self, address_or_ble_device: Union[BLEDevice, str], **kwargs):
super(BleakClientDotNet, self).__init__(address_or_ble_device, **kwargs)
# Backend specific. Python.NET objects.
if isinstance(address_or_ble_device, BLEDevice):
self._device_info = address_or_ble_device.details.BluetoothAd... | def __init__(self, address_or_ble_device: Union[BLEDevice, str], **kwargs):
super(BleakClientDotNet, self).__init__(address_or_ble_device, **kwargs)
# Backend specific. Python.NET objects.
if isinstance(address_or_ble_device, BLEDevice):
self._device_info = address_or_ble_device.details.BluetoothAd... | https://github.com/hbldh/bleak/issues/313 | Connecting to mac: [mac here]
Poking services...
Disconnect on device end now...
0...
1...
2...
3...
4...
Waiting for device to indicate disconnection... ensure it is ready to reconnect
0...
1...
2...
3...
4...
5...
6...
7...
8...
9...
10...
11...
12...
13...
14...
Reconnecting...
Poking services...
Disconnecting...
Wa... | AttributeError |
async def connect(self, **kwargs) -> bool:
"""Connect to the specified GATT server.
Keyword Args:
timeout (float): Timeout for required ``BleakScanner.find_device_by_address`` call. Defaults to 10.0.
Returns:
Boolean representing connection status.
"""
# Create a new BleakBridge h... | async def connect(self, **kwargs) -> bool:
"""Connect to the specified GATT server.
Keyword Args:
timeout (float): Timeout for required ``BleakScanner.find_device_by_address`` call. Defaults to 10.0.
Returns:
Boolean representing connection status.
"""
# Create a new BleakBridge h... | https://github.com/hbldh/bleak/issues/313 | Connecting to mac: [mac here]
Poking services...
Disconnect on device end now...
0...
1...
2...
3...
4...
Waiting for device to indicate disconnection... ensure it is ready to reconnect
0...
1...
2...
3...
4...
5...
6...
7...
8...
9...
10...
11...
12...
13...
14...
Reconnecting...
Poking services...
Disconnecting...
Wa... | AttributeError |
def _ConnectionStatusChanged_Handler(sender, args):
logger.debug("_ConnectionStatusChanged_Handler: %d", sender.ConnectionStatus)
if sender.ConnectionStatus == BluetoothConnectionStatus.Disconnected:
if self._disconnected_callback:
loop.call_soon_threadsafe(self._disconnected_callback, self)... | def _ConnectionStatusChanged_Handler(sender, args):
logger.debug("_ConnectionStatusChanged_Handler: %d", sender.ConnectionStatus)
if (
sender.ConnectionStatus == BluetoothConnectionStatus.Disconnected
and self._disconnected_callback
):
loop.call_soon_threadsafe(self._disconnected_cal... | https://github.com/hbldh/bleak/issues/313 | Connecting to mac: [mac here]
Poking services...
Disconnect on device end now...
0...
1...
2...
3...
4...
Waiting for device to indicate disconnection... ensure it is ready to reconnect
0...
1...
2...
3...
4...
5...
6...
7...
8...
9...
10...
11...
12...
13...
14...
Reconnecting...
Poking services...
Disconnecting...
Wa... | AttributeError |
async def disconnect(self) -> bool:
"""Disconnect from the specified GATT server.
Returns:
Boolean representing if device is disconnected.
Raises:
asyncio.TimeoutError: If device did not disconnect with 10 seconds.
"""
logger.debug("Disconnecting from BLE device...")
# Remove ... | async def disconnect(self) -> bool:
"""Disconnect from the specified GATT server.
Returns:
Boolean representing if device is disconnected.
"""
logger.debug("Disconnecting from BLE device...")
# Remove notifications. Remove them first in the BleakBridge and then clear
# remaining notifi... | https://github.com/hbldh/bleak/issues/313 | Connecting to mac: [mac here]
Poking services...
Disconnect on device end now...
0...
1...
2...
3...
4...
Waiting for device to indicate disconnection... ensure it is ready to reconnect
0...
1...
2...
3...
4...
5...
6...
7...
8...
9...
10...
11...
12...
13...
14...
Reconnecting...
Poking services...
Disconnecting...
Wa... | AttributeError |
async def get_discovered_devices(self) -> List[BLEDevice]:
found = []
peripherals = self._manager.central_manager.retrievePeripheralsWithIdentifiers_(
NSArray(self._identifiers.keys()),
)
for i, peripheral in enumerate(peripherals):
address = peripheral.identifier().UUIDString()
... | async def get_discovered_devices(self) -> List[BLEDevice]:
found = []
peripherals = self._manager.central_manager.retrievePeripheralsWithIdentifiers_(
self._identifiers.keys(),
)
for i, peripheral in enumerate(peripherals):
address = peripheral.identifier().UUIDString()
name = p... | https://github.com/hbldh/bleak/issues/331 | 2020-10-12 22:16:31.801 Python[3820:332546] *** Assertion failure in -[CBCentralManager retrievePeripheralsWithIdentifiers:], /BuildRoot/Library/Caches/com.apple.xbs/Sources/CoreBluetooth/CoreBluetooth-102.23/CBCentralManager.m:203
Traceback (most recent call last):
File "bleak_test3.py", line 52, in <module>
loop.run_... | objc.error |
async def is_connected(self) -> bool:
"""Check connection status between this client and the server.
Returns:
Boolean representing connection status.
"""
# TODO: Listen to connected property changes.
is_connected = False
try:
is_connected = await self._bus.callRemote(
... | async def is_connected(self) -> bool:
"""Check connection status between this client and the server.
Returns:
Boolean representing connection status.
"""
# TODO: Listen to connected property changes.
is_connected = False
try:
is_connected = await self._bus.callRemote(
... | https://github.com/hbldh/bleak/issues/310 | client = BleakClient(address)
await client.connect()
await client.disconnect()
Traceback (most recent call last):
File "/home/pi/venv/lib/python3.7/site-packages/aioconsole/execute.py", line 87, in aexec
result, new_local = await coro
File "<aexec>", line 2, in __corofn
File "/home/pi/venv/lib/python3.7/site-packages/... | txdbus.error.RemoteError |
async def is_connected(self) -> bool:
"""Check connection status between this client and the server.
Returns:
Boolean representing connection status.
"""
# TODO: Listen to connected property changes.
is_connected = False
try:
is_connected = await self._bus.callRemote(
... | async def is_connected(self) -> bool:
"""Check connection status between this client and the server.
Returns:
Boolean representing connection status.
"""
# TODO: Listen to connected property changes.
return await self._bus.callRemote(
self._device_path,
"Get",
inter... | https://github.com/hbldh/bleak/issues/259 | INFO:__main__:Connected: True
True
True
...
True
True
DEBUG:bleak.backends.bluezdbus.client:DBUS: path: /org/bluez/hci0/dev_REDACTED, domain: org.bluez.Device1, body: {'ServicesResolved': False, 'Connected': False}
DEBUG:bleak.backends.bluezdbus.client:Device REDACTED disconnected.
DEBUG:bleak.backends.bluezdbus.client... | AttributeError |
async def scanForPeripherals_(self, scan_options) -> List[CBPeripheral]:
"""
Scan for peripheral devices
scan_options = { service_uuids, timeout }
"""
# remove old
self.devices = {}
service_uuids = []
if "service_uuids" in scan_options:
service_uuids_str = scan_options["service_u... | async def scanForPeripherals_(self, scan_options) -> List[CBPeripheral]:
"""
Scan for peripheral devices
scan_options = { service_uuids, timeout }
"""
# remove old
self.devices = {}
service_uuids = []
if "service_uuids" in scan_options:
service_uuids_str = scan_options["service_u... | https://github.com/hbldh/bleak/issues/234 | $ python scanner.py
Traceback (most recent call last):
File "scanner.py", line 12, in <module>
loop.run_until_complete(run())
File "/usr/local/Cellar/python/3.7.0/Frameworks/Python.framework/Versions/3.7/lib/python3.7/asyncio/base_events.py", line 568, in run_until_complete
return future.result()
File "scanner.py", lin... | AttributeError |
async def discover(
timeout: float = 5.0, loop: AbstractEventLoop = None, **kwargs
) -> List[BLEDevice]:
"""Perform a Bluetooth LE Scan using Windows.Devices.Bluetooth.Advertisement
Args:
timeout (float): Time to scan for.
loop (Event Loop): The event loop to use.
Keyword Args:
... | async def discover(
timeout: float = 5.0, loop: AbstractEventLoop = None, **kwargs
) -> List[BLEDevice]:
"""Perform a Bluetooth LE Scan using Windows.Devices.Bluetooth.Advertisement
Args:
timeout (float): Time to scan for.
loop (Event Loop): The event loop to use.
Keyword Args:
... | https://github.com/hbldh/bleak/issues/87 | Traceback (most recent call last):
File "[my script].py", line 140, in <module>
loop.run_until_complete(scan_loop())
File "[My user folder]\Anaconda3\lib\asyncio\base_events.py", line 584, in run_until_complete
return future.result()
File "[my script].py", line 102, in scan_loop
devices = await discover(device="hci0", ... | RuntimeError |
async def _cleanup(self) -> None:
for rule_name, rule_id in self._rules.items():
logger.debug("Removing rule {0}, ID: {1}".format(rule_name, rule_id))
try:
await self._bus.delMatch(rule_id).asFuture(self.loop)
except Exception as e:
logger.error(
"Coul... | async def _cleanup(self) -> None:
for rule_name, rule_id in self._rules.items():
logger.debug("Removing rule {0}, ID: {1}".format(rule_name, rule_id))
try:
await self._bus.delMatch(rule_id).asFuture(self.loop)
except Exception as e:
logger.error(
"Coul... | https://github.com/hbldh/bleak/issues/145 | INFO:bleak.backends.bluezdbus.client:605: GATT Char Properties Changed: gorg/bluez/hci0/dev_F2_1F_2B_52_48_9E/service000e/char0017 | [{'Value': [23, 8, 160]}, []]
DEBUG:bleak.backends.bluezdbus.client:597: DBUS: path: gorg/bluez/hci0/dev_F2_1F_2B_52_48_9E/service000e/char0017, domain: org.bluez.GattCharacteristic1, bod... | txdbus.error.RemoteError |
async def connect(self, **kwargs) -> bool:
"""Connect to the specified GATT server.
Keyword Args:
timeout (float): Timeout for required ``discover`` call. Defaults to 2.0.
Returns:
Boolean representing connection status.
"""
# A Discover must have been run before connecting to an... | async def connect(self, **kwargs) -> bool:
"""Connect to the specified GATT server.
Keyword Args:
timeout (float): Timeout for required ``discover`` call. Defaults to 0.1.
Returns:
Boolean representing connection status.
"""
# A Discover must have been run before connecting to an... | https://github.com/hbldh/bleak/issues/101 | /Users/zaytsev/PycharmProjects/bluetooth/venv/bin/python /Users/zaytsev/PycharmProjects/bluetooth/bleak_demo.py
DEBUG:bleak.backends.corebluetooth.CentralManagerDelegate:Bluetooth powered on
DEBUG:bleak.backends.corebluetooth.CentralManagerDelegate:Discovered device A0E49DB2-B7F1-4A65-AB2E-D75121192329: Unknown @ RSSI:... | bleak.exc.BleakError |
async def _cleanup(self) -> None:
for rule_name, rule_id in self._rules.items():
logger.debug("Removing rule {0}, ID: {1}".format(rule_name, rule_id))
try:
await self._bus.delMatch(rule_id).asFuture(self.loop)
except Exception as e:
logger.error(
"Coul... | async def _cleanup(self) -> None:
for rule_name, rule_id in self._rules.items():
logger.debug("Removing rule {0}, ID: {1}".format(rule_name, rule_id))
await self._bus.delMatch(rule_id).asFuture(self.loop)
await asyncio.gather(*(self.stop_notify(_uuid) for _uuid in self._subscriptions))
| https://github.com/hbldh/bleak/issues/101 | /Users/zaytsev/PycharmProjects/bluetooth/venv/bin/python /Users/zaytsev/PycharmProjects/bluetooth/bleak_demo.py
DEBUG:bleak.backends.corebluetooth.CentralManagerDelegate:Bluetooth powered on
DEBUG:bleak.backends.corebluetooth.CentralManagerDelegate:Discovered device A0E49DB2-B7F1-4A65-AB2E-D75121192329: Unknown @ RSSI:... | bleak.exc.BleakError |
async def get_services(self) -> BleakGATTServiceCollection:
"""Get all services registered for this GATT server.
Returns:
A :py:class:`bleak.backends.service.BleakGATTServiceCollection` with this device's services tree.
"""
if self._services_resolved:
return self.services
sleep_loo... | async def get_services(self) -> BleakGATTServiceCollection:
"""Get all services registered for this GATT server.
Returns:
A :py:class:`bleak.backends.service.BleakGATTServiceCollection` with this device's services tree.
"""
if self._services_resolved:
return self.services
while Tru... | https://github.com/hbldh/bleak/issues/101 | /Users/zaytsev/PycharmProjects/bluetooth/venv/bin/python /Users/zaytsev/PycharmProjects/bluetooth/bleak_demo.py
DEBUG:bleak.backends.corebluetooth.CentralManagerDelegate:Bluetooth powered on
DEBUG:bleak.backends.corebluetooth.CentralManagerDelegate:Discovered device A0E49DB2-B7F1-4A65-AB2E-D75121192329: Unknown @ RSSI:... | bleak.exc.BleakError |
async def read_gatt_char(self, _uuid: str, **kwargs) -> bytearray:
"""Perform read operation on the specified GATT characteristic.
Args:
_uuid (str or UUID): The uuid of the characteristics to read from.
Returns:
(bytearray) The read data.
"""
characteristic = self.services.get_ch... | async def read_gatt_char(self, _uuid: str, **kwargs) -> bytearray:
"""Perform read operation on the specified GATT characteristic.
Args:
_uuid (str or UUID): The uuid of the characteristics to read from.
Returns:
(bytearray) The read data.
"""
characteristic = self.services.get_ch... | https://github.com/hbldh/bleak/issues/101 | /Users/zaytsev/PycharmProjects/bluetooth/venv/bin/python /Users/zaytsev/PycharmProjects/bluetooth/bleak_demo.py
DEBUG:bleak.backends.corebluetooth.CentralManagerDelegate:Bluetooth powered on
DEBUG:bleak.backends.corebluetooth.CentralManagerDelegate:Discovered device A0E49DB2-B7F1-4A65-AB2E-D75121192329: Unknown @ RSSI:... | bleak.exc.BleakError |
def _properties_changed_callback(self, message):
"""Notification handler.
In the BlueZ DBus API, notifications come as
PropertiesChanged callbacks on the GATT Characteristic interface
that StartNotify has been called on.
Args:
message (): The PropertiesChanged DBus signal message relaying
... | def _properties_changed_callback(self, message):
"""Notification handler.
In the BlueZ DBus API, notifications come as
PropertiesChanged callbacks on the GATT Characteristic interface
that StartNotify has been called on.
Args:
message (): The PropertiesChanged DBus signal message relaying
... | https://github.com/hbldh/bleak/issues/101 | /Users/zaytsev/PycharmProjects/bluetooth/venv/bin/python /Users/zaytsev/PycharmProjects/bluetooth/bleak_demo.py
DEBUG:bleak.backends.corebluetooth.CentralManagerDelegate:Bluetooth powered on
DEBUG:bleak.backends.corebluetooth.CentralManagerDelegate:Discovered device A0E49DB2-B7F1-4A65-AB2E-D75121192329: Unknown @ RSSI:... | bleak.exc.BleakError |
def _device_info(path, props):
try:
name = props.get("Name", props.get("Alias", path.split("/")[-1]))
address = props.get("Address", None)
if address is None:
try:
address = path[-17:].replace("_", ":")
if not validate_mac_address(address):
... | def _device_info(path, props):
try:
name = props.get("Name", props.get("Alias", path.split("/")[-1]))
address = props.get("Address", None)
if address is None:
try:
address = path[-17:].replace("_", ":")
if not validate_mac_address(address):
... | https://github.com/hbldh/bleak/issues/101 | /Users/zaytsev/PycharmProjects/bluetooth/venv/bin/python /Users/zaytsev/PycharmProjects/bluetooth/bleak_demo.py
DEBUG:bleak.backends.corebluetooth.CentralManagerDelegate:Bluetooth powered on
DEBUG:bleak.backends.corebluetooth.CentralManagerDelegate:Discovered device A0E49DB2-B7F1-4A65-AB2E-D75121192329: Unknown @ RSSI:... | bleak.exc.BleakError |
async def discover(timeout=5.0, loop=None, **kwargs):
"""Discover nearby Bluetooth Low Energy devices.
Args:
timeout (float): Duration to scan for.
loop (asyncio.AbstractEventLoop): Optional event loop to use.
Keyword Args:
device (str): Bluetooth device to use for discovery.
... | async def discover(timeout=5.0, loop=None, **kwargs):
"""Discover nearby Bluetooth Low Energy devices.
Args:
timeout (float): Duration to scan for.
loop (asyncio.AbstractEventLoop): Optional event loop to use.
Keyword Args:
device (str): Bluetooth device to use for discovery.
... | https://github.com/hbldh/bleak/issues/101 | /Users/zaytsev/PycharmProjects/bluetooth/venv/bin/python /Users/zaytsev/PycharmProjects/bluetooth/bleak_demo.py
DEBUG:bleak.backends.corebluetooth.CentralManagerDelegate:Bluetooth powered on
DEBUG:bleak.backends.corebluetooth.CentralManagerDelegate:Discovered device A0E49DB2-B7F1-4A65-AB2E-D75121192329: Unknown @ RSSI:... | bleak.exc.BleakError |
def __init__(self, address, loop=None, **kwargs):
self.address = address
self.loop = loop if loop else asyncio.get_event_loop()
self.services = BleakGATTServiceCollection()
self._services_resolved = False
self._notification_callbacks = {}
self._timeout = kwargs.get("timeout", 2.0)
| def __init__(self, address, loop=None, **kwargs):
self.address = address
self.loop = loop if loop else asyncio.get_event_loop()
self.services = BleakGATTServiceCollection()
self._services_resolved = False
self._notification_callbacks = {}
| https://github.com/hbldh/bleak/issues/101 | /Users/zaytsev/PycharmProjects/bluetooth/venv/bin/python /Users/zaytsev/PycharmProjects/bluetooth/bleak_demo.py
DEBUG:bleak.backends.corebluetooth.CentralManagerDelegate:Bluetooth powered on
DEBUG:bleak.backends.corebluetooth.CentralManagerDelegate:Discovered device A0E49DB2-B7F1-4A65-AB2E-D75121192329: Unknown @ RSSI:... | bleak.exc.BleakError |
async def connect(self, **kwargs) -> bool:
"""Connect to a specified Peripheral
Keyword Args:
timeout (float): Timeout for required ``discover`` call. Defaults to 2.0.
Returns:
Boolean representing connection status.
"""
timeout = kwargs.get("timeout", self._timeout)
devices =... | async def connect(self, **kwargs) -> bool:
"""Connect to a specified Peripheral
Keyword Args:
timeout (float): Timeout for required ``discover`` call. Defaults to 2.0.
Returns:
Boolean representing connection status.
"""
devices = await discover(timeout=kwargs.get("timeout", 5.0),... | https://github.com/hbldh/bleak/issues/101 | /Users/zaytsev/PycharmProjects/bluetooth/venv/bin/python /Users/zaytsev/PycharmProjects/bluetooth/bleak_demo.py
DEBUG:bleak.backends.corebluetooth.CentralManagerDelegate:Bluetooth powered on
DEBUG:bleak.backends.corebluetooth.CentralManagerDelegate:Discovered device A0E49DB2-B7F1-4A65-AB2E-D75121192329: Unknown @ RSSI:... | bleak.exc.BleakError |
async def get_services(self) -> BleakGATTServiceCollection:
"""Get all services registered for this GATT server.
Returns:
A :py:class:`bleak.backends.service.BleakGATTServiceCollection` with this device's services tree.
"""
if self._services is not None:
return self._services
logge... | async def get_services(self) -> BleakGATTServiceCollection:
"""Get all services registered for this GATT server.
Returns:
A :py:class:`bleak.backends.service.BleakGATTServiceCollection` with this device's services tree.
"""
if self._services != None:
return self._services
logger.de... | https://github.com/hbldh/bleak/issues/101 | /Users/zaytsev/PycharmProjects/bluetooth/venv/bin/python /Users/zaytsev/PycharmProjects/bluetooth/bleak_demo.py
DEBUG:bleak.backends.corebluetooth.CentralManagerDelegate:Bluetooth powered on
DEBUG:bleak.backends.corebluetooth.CentralManagerDelegate:Discovered device A0E49DB2-B7F1-4A65-AB2E-D75121192329: Unknown @ RSSI:... | bleak.exc.BleakError |
async def connect(self, **kwargs) -> bool:
"""Connect to the specified GATT server.
Keyword Args:
timeout (float): Timeout for required ``discover`` call. Defaults to 2.0.
Returns:
Boolean representing connection status.
"""
# Try to find the desired device.
timeout = kwargs.g... | async def connect(self, **kwargs) -> bool:
"""Connect to the specified GATT server.
Keyword Args:
timeout (float): Timeout for required ``discover`` call. Defaults to 2.0.
Returns:
Boolean representing connection status.
"""
# Try to find the desired device.
devices = await di... | https://github.com/hbldh/bleak/issues/101 | /Users/zaytsev/PycharmProjects/bluetooth/venv/bin/python /Users/zaytsev/PycharmProjects/bluetooth/bleak_demo.py
DEBUG:bleak.backends.corebluetooth.CentralManagerDelegate:Bluetooth powered on
DEBUG:bleak.backends.corebluetooth.CentralManagerDelegate:Discovered device A0E49DB2-B7F1-4A65-AB2E-D75121192329: Unknown @ RSSI:... | bleak.exc.BleakError |
async def discover(
timeout: float = 5.0, loop: AbstractEventLoop = None, **kwargs
) -> List[BLEDevice]:
"""Perform a Bluetooth LE Scan using Windows.Devices.Bluetooth.Advertisement
Args:
timeout (float): Time to scan for.
loop (Event Loop): The event loop to use.
Keyword Args:
... | async def discover(
timeout: float = 5.0, loop: AbstractEventLoop = None, **kwargs
) -> List[BLEDevice]:
"""Perform a Bluetooth LE Scan using Windows.Devices.Bluetooth.Advertisement
Args:
timeout (float): Time to scan for.
loop (Event Loop): The event loop to use.
Keyword Args:
... | https://github.com/hbldh/bleak/issues/101 | /Users/zaytsev/PycharmProjects/bluetooth/venv/bin/python /Users/zaytsev/PycharmProjects/bluetooth/bleak_demo.py
DEBUG:bleak.backends.corebluetooth.CentralManagerDelegate:Bluetooth powered on
DEBUG:bleak.backends.corebluetooth.CentralManagerDelegate:Discovered device A0E49DB2-B7F1-4A65-AB2E-D75121192329: Unknown @ RSSI:... | bleak.exc.BleakError |
def AdvertisementWatcher_Received(sender, e):
if sender == watcher:
logger.debug("Received {0}.".format(_format_event_args(e)))
if e.AdvertisementType == BluetoothLEAdvertisementType.ScanResponse:
if e.BluetoothAddress not in scan_responses:
scan_responses[e.BluetoothAddr... | def AdvertisementWatcher_Received(sender, e):
if sender == watcher:
logger.debug("Received {0}.".format(_format_event_args(e)))
if e.BluetoothAddress not in devices:
devices[e.BluetoothAddress] = e
| https://github.com/hbldh/bleak/issues/101 | /Users/zaytsev/PycharmProjects/bluetooth/venv/bin/python /Users/zaytsev/PycharmProjects/bluetooth/bleak_demo.py
DEBUG:bleak.backends.corebluetooth.CentralManagerDelegate:Bluetooth powered on
DEBUG:bleak.backends.corebluetooth.CentralManagerDelegate:Discovered device A0E49DB2-B7F1-4A65-AB2E-D75121192329: Unknown @ RSSI:... | bleak.exc.BleakError |
async def run(address, loop, debug=False):
if debug:
import sys
# loop.set_debug(True)
# l = logging.getLogger("asyncio")
# l.setLevel(logging.DEBUG)
# h = logging.StreamHandler(sys.stdout)
# h.setLevel(logging.DEBUG)
# l.addHandler(h)
async with BleakCl... | async def run(address, loop, debug=False):
if debug:
import sys
loop.set_debug(True)
l = logging.getLogger("asyncio")
l.setLevel(logging.DEBUG)
h = logging.StreamHandler(sys.stdout)
h.setLevel(logging.DEBUG)
l.addHandler(h)
async with BleakClient(address... | https://github.com/hbldh/bleak/issues/101 | /Users/zaytsev/PycharmProjects/bluetooth/venv/bin/python /Users/zaytsev/PycharmProjects/bluetooth/bleak_demo.py
DEBUG:bleak.backends.corebluetooth.CentralManagerDelegate:Bluetooth powered on
DEBUG:bleak.backends.corebluetooth.CentralManagerDelegate:Discovered device A0E49DB2-B7F1-4A65-AB2E-D75121192329: Unknown @ RSSI:... | bleak.exc.BleakError |
async def discover(timeout=5.0, loop=None, **kwargs):
"""Discover nearby Bluetooth Low Energy devices.
Args:
timeout (float): Duration to scan for.
loop (asyncio.AbstractEventLoop): Optional event loop to use.
Keyword Args:
device (str): Bluetooth device to use for discovery.
... | async def discover(timeout=5.0, loop=None, **kwargs):
"""Discover nearby Bluetooth Low Energy devices.
Args:
timeout (float): Duration to scan for.
loop (asyncio.AbstractEventLoop): Optional event loop to use.
Keyword Args:
device (str): Bluetooth device to use for discovery.
... | https://github.com/hbldh/bleak/issues/91 | Traceback (most recent call last):
File "discover.py", line 29, in <module>
loop.run_until_complete(run())
File "/usr/lib64/python3.7/asyncio/base_events.py", line 584, in run_until_complete
return future.result()
File "discover.py", line 22, in run
devices = await discover(timeout=1)
File "/home/joe/code/proglove/pyth... | txdbus.error.RemoteError |
def __init__(self, address, loop=None, **kwargs):
super(BleakClientBlueZDBus, self).__init__(address, loop, **kwargs)
self.device = kwargs.get("device") if kwargs.get("device") else "hci0"
self.address = address
# Backend specific, TXDBus objects and data
self._device_path = None
self._bus = No... | def __init__(self, address, loop=None, **kwargs):
super(BleakClientBlueZDBus, self).__init__(address, loop, **kwargs)
self.device = kwargs.get("device") if kwargs.get("device") else "hci0"
self.address = address
# Backend specific, TXDBus objects and data
self._device_path = None
self._bus = No... | https://github.com/hbldh/bleak/issues/91 | Traceback (most recent call last):
File "discover.py", line 29, in <module>
loop.run_until_complete(run())
File "/usr/lib64/python3.7/asyncio/base_events.py", line 584, in run_until_complete
return future.result()
File "discover.py", line 22, in run
devices = await discover(timeout=1)
File "/home/joe/code/proglove/pyth... | txdbus.error.RemoteError |
async def connect(self, **kwargs) -> bool:
"""Connect to the specified GATT server.
Keyword Args:
timeout (float): Timeout for required ``discover`` call. Defaults to 0.1.
Returns:
Boolean representing connection status.
"""
# A Discover must have been run before connecting to an... | async def connect(self, **kwargs) -> bool:
"""Connect to the specified GATT server.
Keyword Args:
timeout (float): Timeout for required ``discover`` call. Defaults to 0.1.
Returns:
Boolean representing connection status.
"""
# A Discover must have been run before connecting to an... | https://github.com/hbldh/bleak/issues/91 | Traceback (most recent call last):
File "discover.py", line 29, in <module>
loop.run_until_complete(run())
File "/usr/lib64/python3.7/asyncio/base_events.py", line 584, in run_until_complete
return future.result()
File "discover.py", line 22, in run
devices = await discover(timeout=1)
File "/home/joe/code/proglove/pyth... | txdbus.error.RemoteError |
async def disconnect(self) -> bool:
"""Disconnect from the specified GATT server.
Returns:
Boolean representing connection status.
"""
logger.debug("Disconnecting from BLE device...")
await self._cleanup()
await self._bus.callRemote(
self._device_path,
"Disconnect",
... | async def disconnect(self) -> bool:
"""Disconnect from the specified GATT server.
Returns:
Boolean representing connection status.
"""
logger.debug("Disconnecting from BLE device...")
for rule_name, rule_id in self._rules.items():
logger.debug("Removing rule {0}, ID: {1}".format(ru... | https://github.com/hbldh/bleak/issues/91 | Traceback (most recent call last):
File "discover.py", line 29, in <module>
loop.run_until_complete(run())
File "/usr/lib64/python3.7/asyncio/base_events.py", line 584, in run_until_complete
return future.result()
File "discover.py", line 22, in run
devices = await discover(timeout=1)
File "/home/joe/code/proglove/pyth... | txdbus.error.RemoteError |
async def write_gatt_char(
self, _uuid: str, data: bytearray, response: bool = False
) -> None:
"""Perform a write operation on the specified GATT characteristic.
Args:
_uuid (str or UUID): The uuid of the characteristics to write to.
data (bytes or bytearray): The data to send.
res... | async def write_gatt_char(
self, _uuid: str, data: bytearray, response: bool = False
) -> None:
"""Perform a write operation on the specified GATT characteristic.
Args:
_uuid (str or UUID): The uuid of the characteristics to write to.
data (bytes or bytearray): The data to send.
res... | https://github.com/hbldh/bleak/issues/91 | Traceback (most recent call last):
File "discover.py", line 29, in <module>
loop.run_until_complete(run())
File "/usr/lib64/python3.7/asyncio/base_events.py", line 584, in run_until_complete
return future.result()
File "discover.py", line 22, in run
devices = await discover(timeout=1)
File "/home/joe/code/proglove/pyth... | txdbus.error.RemoteError |
async def start_notify(
self, _uuid: str, callback: Callable[[str, Any], Any], **kwargs
) -> None:
"""Activate notifications/indications on a characteristic.
Callbacks must accept two inputs. The first will be a uuid string
object and the second will be a bytearray.
.. code-block:: python
... | async def start_notify(
self, _uuid: str, callback: Callable[[str, Any], Any], **kwargs
) -> None:
"""Activate notifications/indications on a characteristic.
Callbacks must accept two inputs. The first will be a uuid string
object and the second will be a bytearray.
.. code-block:: python
... | https://github.com/hbldh/bleak/issues/91 | Traceback (most recent call last):
File "discover.py", line 29, in <module>
loop.run_until_complete(run())
File "/usr/lib64/python3.7/asyncio/base_events.py", line 584, in run_until_complete
return future.result()
File "discover.py", line 22, in run
devices = await discover(timeout=1)
File "/home/joe/code/proglove/pyth... | txdbus.error.RemoteError |
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